{"id":3555,"date":"2023-07-16T21:03:21","date_gmt":"2023-07-16T21:03:21","guid":{"rendered":"https:\/\/statorials.org\/tr\/rde-svmyi-ciz\/"},"modified":"2023-07-16T21:03:21","modified_gmt":"2023-07-16T21:03:21","slug":"rde-svmyi-ciz","status":"publish","type":"post","link":"https:\/\/statorials.org\/tr\/rde-svmyi-ciz\/","title":{"rendered":"R'de svm nesnesi nas\u0131l \u00e7izilir (\u00f6rnekle)"},"content":{"rendered":"

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R’de bir destek vekt\u00f6r makinesi (SVM) nesnesini \u00e7izmek i\u00e7in a\u015fa\u011f\u0131daki temel s\u00f6zdizimini kullanabilirsiniz:<\/span><\/p>\n

 library<\/span> (e1071)\n\nplot(svm_model, df)\n<\/strong><\/pre>\n
 Bu \u00f6rnekte df<\/strong> , veri \u00e7er\u00e7evesi ad\u0131d\u0131r ve svm_model,<\/strong> svm()<\/strong> i\u015flevini kullanan bir destek vekt\u00f6r makinesidir.<\/span><\/p>\n
 A\u015fa\u011f\u0131daki \u00f6rnek, bu s\u00f6zdiziminin pratikte nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6sterir.<\/span><\/p>\n
 \u00d6rnek: R’de bir SVM nesnesi nas\u0131l \u00e7izilir<\/strong><\/span><\/h2>\n
 R’de \u00e7e\u015fitli basketbol oyuncular\u0131 hakk\u0131nda bilgi i\u00e7eren a\u015fa\u011f\u0131daki veri \u00e7er\u00e7evesine sahip oldu\u011fumuzu varsayal\u0131m:<\/span><\/p>\n
 #create data frame\n<\/span>df <- data. frame<\/span> (points = c(4, 5, 5, 7, 8, 12, 15, 22, 25, 29),\n                 assists = c(3, 4, 6, 8, 5, 6, 5, 6, 8, 12),\n                 good = factor(c(0, 0, 0, 1, 0, 1, 0, 1, 1, 1)))\n\n#view data frame\n<\/span>df\n\n   points assists good\n1 4 3 0\n2 5 4 0\n3 5 6 0\n4 7 8 1\n5 8 5 0\n6 12 6 1\n7 15 5 0\n8 22 6 1\n9 25 8 1\n10 29 12 1<\/strong><\/span><\/pre>\n
 Diyelim ki de\u011fi\u015fken noktalar\u0131<\/strong> kullanan ve bir oyuncunun iyi<\/strong> olup olmad\u0131\u011f\u0131n\u0131 tahmin etmeye yard\u0131mc\u0131 olan<\/strong> bir destek vekt\u00f6r makinesi olu\u015fturmak istiyoruz (0 = hay\u0131r, 1 = evet).<\/span><\/p>\n
 Destek vekt\u00f6r makinesine s\u0131\u011fd\u0131rmak i\u00e7in a\u015fa\u011f\u0131daki kodu kullanabilir ve ard\u0131ndan sonu\u00e7lar\u0131 \u00e7izebiliriz:<\/span> <\/p>\n
 library<\/span> (e1071)<\/span>\n\n#fit support vector machine\n<\/span>model = svm(good ~ points + assists, data = df)\n\n#plot support vector machine\n<\/span>plot(model, df)<\/span><\/span><\/strong> <\/pre>\n
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 Grafik, asist<\/strong> de\u011fi\u015fkeninin de\u011ferlerini x ekseninde, puan<\/strong> de\u011fi\u015fkeninin de\u011ferlerini y ekseninde g\u00f6r\u00fcnt\u00fcler ve bir oyuncunun iyi (k\u0131rm\u0131z\u0131) veya iyi olaca\u011f\u0131n\u0131n tahmin edilip edilmedi\u011fini g\u00f6stermek i\u00e7in iki farkl\u0131 renk kullan\u0131r. de\u011fil (sar\u0131).<\/span><\/p>\n
 \u00c7izim i\u00e7in farkl\u0131 bir renk paleti kullanmak amac\u0131yla, arsa()<\/strong> i\u015flevindeki color.palette<\/strong> ba\u011f\u0131ms\u0131z de\u011fi\u015fkenini kullanabilece\u011finizi unutmay\u0131n.<\/span><\/p>\n
 \u00d6rne\u011fin heat.colors<\/strong> renk paletini kullanmay\u0131 se\u00e7ebiliriz:<\/span> <\/p>\n
 library<\/span> (e1071)<\/span>\n\n#fit support vector machine\n<\/span>model = svm(good ~ points + assists, data = df)\n\n#plot support vector machine using different color palette\n<\/span>plot(model, df, color. palette<\/span> = heat. colors<\/span> )<\/span><\/span><\/strong> <\/pre>\n
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 color.palette<\/strong> arg\u00fcman\u0131 i\u00e7in di\u011fer pop\u00fcler se\u00e7enekler \u015funlard\u0131r:<\/span><\/p>\n